A new recognition method of handwritten Chinese characters by support vector machine is presented.Support vector machines(SVM) operate on the principle of structure risk minimization which not only keeps the empirical risk minimal but also controls VC confidence of discriminant functions

hence a better generalization ability is guaranteed.In this paper

the problems to be solved while applying SVM in Chinese character recognition are addressed at first

and then a two stage of recognition scheme is suggested.Finally

experimental results on 1034 categories of Chinese character from 120 sets of samples are given.For the Polynomial kernel SVM

a 3.38% average increment of recognition rate is obtained showing the efficiency of the proposed approach.